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In 2016, the ‘FAIR Guiding Principles for scientific data management and stewardship’ were published in Scientific Data. The authors intended to provide guidelines to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets. The principles emphasise machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data with none or minimal human intervention) because humans increasingly rely on computational support to deal with data as a result of the increase in volume, complexity, and creation speed of data.

A practical “how to” guidance to go FAIR can be found in the Three-point FAIRification Framework.

Findable
The first step in (re)using data is to find them. Metadata and data should be easy to find for both humans and computers. Machine-readable metadata are essential for automatic discovery of datasets and services, so this is an essential component of the FAIRification process.

F1. (Meta)data are assigned a globally unique and persistent identifier

F2. Data are described with rich metadata (defined by R1 below)

F3. Metadata clearly and explicitly include the identifier of the data they describe

F4. (Meta)data are registered or indexed in a searchable resource

Accessible
Once the user finds the required data, she/he/they need to know how they can be accessed, possibly including authentication and authorisation.

A1. (Meta)data are retrievable by their identifier using a standardised communications protocol

A1.1 The protocol is open, free, and universally implementable

A1.2 The protocol allows for an authentication and authorisation procedure, where necessary

A2. Metadata are accessible, even when the data are no longer available

Interoperable
The data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing.

I1. (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.

I2. (Meta)data use vocabularies that follow FAIR principles

I3. (Meta)data include qualified references to other (meta)data

Reusable
The ultimate goal of FAIR is to optimise the reuse of data. To achieve this, metadata and data should be well-described so that they can be replicated and/or combined in different settings.

R1. (Meta)data are richly described with a plurality of accurate and relevant attributes

R1.1. (Meta)data are released with a clear and accessible data usage license

R1.2. (Meta)data are associated with detailed provenance

R1.3. (Meta)data meet domain-relevant community standards

The principles refer to three types of entities: data (or any digital object), metadata (information about that digital object), and infrastructure. For instance, principle F4 defines that both metadata and data are registered or indexed in a searchable resource (the infrastructure component).

 RDA

RDA is a modern cataloguing standard for describing and providinbg 

Daily Quiz

Which of the following is an example of  metadata standard commonly used in digital libraries.

DRM (Digital Rights Management)

Z39.50

Dublin Core

ISBD

Dublin Core is a widely used metadata standard in digital libraries

it provides a set of simple and general elements for resource description

it is maintained by the Dublin core metadata initiative (DCMI)

it is used for interoperability and easy information exchange

DRM--Technology for copyright protection

Z39.50-Protocol for information retrieval (Not metadata standard)

ISBD- Bibliographic description standard (primarily for library cataloguing) 

 

Daily reading

 Notation in library classification

1.What is notation

Notation is a system of symbols used in a classification scheme to represent classes and their relationship

it converts conceptual arrangement of subjects into class marks for arrangement and retrieval

Different schemes use different types of notation

2. Types of Notation

Uses one species of symbols

Ex. DDC uses Arabic numerals (0-9)

Simple and easy to use

500.123 (DDC)

Mixed Notation 

Uses two or more species of symbols (numerals, letters, punctuatuation)

Ex. Colon Classification (CC) Library of congress (LCC) More flexible and expressive 

QA76.73

 3. Hierarchical Notation: Notation reflects the hierarchical arrangement of classes.

Increasing specificity is shown by extension of notation

Ex. DDC 

Science 500

Mathematics 510

Geometry 516 

4.Hospitality in notation:

Capacity of a notation to accommodate new subjects, concepts and subdivisions without disturbing the existing structure.

Hospitality in Array

Insertion of new coordinate classes

Hospitality in chain

Insertion of new subordinate or superordinate  levels.

5.Mnenomics:

Notation is mnemonic when recurring symbols help users remember concepts.

Aids memory and makes notation easy to learn interpret and apply.

Widely used in classification schemes. 

6.Qualities of Good notation

Simplicity: Easy to write and understand

Brevity: Reasonably short

Expressiveness: Reflects useful relationships

Hospitality: Accommodates new subjects

Mnemonics: Assists memory

Uniqueness: Provides clear identification.

7.Notation in major schemes

DDC                          Pure (Arabic numerals)

UDC                          Arabic numerals+auxiliary symbols (mixed)

Library of Congress classification:Mixed/alphaneumeric (letters+numerals)

8.Facts to remember 

Notation represents classes through symbols

Pure notation uses one species of symbols

Mixed notation uses two or more species of symbols

DDC predominantly uses pure numerical notation

Colon classification uses mixed notation 

Hospitatlity = capacity to accommodate new subjects 

Arrary hospitality concerns cordinate classes

chain hospitality concerns hierarchical lvels

Mnemonics make notation easier to remember

9.Pure=One

Mixed= Many

Hospitality=Growth

Mnemonics=Memory

10.The capacity of a classification notation to accommodate new subjects is called

a)Mnemonics

b)Hospitality

c)Enumeration 

d)Collocation 

 

 

Daily Reading

 Journal Impact Factor

Measures the average citations received by recent articles of a Journal.

JIF  in a year X = Citations in year X to items published in X-1 and X-2 

                              -----------------------------------------------------------------

                                Citable items published in X-1 and X-2

 

Ex. Journal Articles   500 citations  .-. 100 citable items = JIF 5.0

      (X-1 & X-2) 

Introduced by 

Eugene Garfield

Published in Journal citation reports

Citation Window

Previous two years

used for 

Journal evaluation and selection 

Daily reading

h-Index, g-index, i10 index

h-index proposed by Jorge E. Hirsch

A scholar has h-index= h when h publications have at least h citations each

ex. 5 papers with at least 5 citations each- h-index=5

balances quantity and quality 

h-index productivity+impact

g-index

proposed by Leo Egghe

Top g publication must receive at least g2 citations in total

ex. for g=5, total citations of top 5 papers must be at least 25

give extra weight to highly cited papers

more weight to highly cited papers 

i10 index

introduced by Google Scholar

counts the number of publications with at least 10 citations

ex. 12 papers with 10+ citations - i10 index=12

easiest and most straightforward indicator

papers cited 10 or more times

H-hirsch

g=greater weight

i10=10 citations 

Daily reading

 Sampling is the process of selecting a representative subset of individuals objects or documents from a larger population for study so that findings can be generalized to the whole

 Probability Sampling

Single random sampling

Systematic sampling

Stratified sampling

Cluster sampling

Multistage sampling

Every member has a known and non-zero chance of being selected 

Non-probability Sampling

Convenience Sampling

Purposive sampling

Quota sampling

Snowball sampling 

Selection is based on researcher's judgement rather than randomization 

 

Daily Reading

 Bibliometrics is the application of mathematical and statistical methods to books articles and other recorded communication to study patterns of publication authorship citations and use.

Uses mathmatical and statistical techniques

Studies publication, authorship, citation and usage patterns

Helps in research evaluation, policy formulation and collection managment.

closely related to Scientometrics Informetrics and Webometrics  

Helps in mapping the growth of literature in a fields

useful for research evaluation and impact assessment

 Lotka's Law

Author Productivity

Describes the distribution of productivity among others

Bradfords Law

Scattering of articles among journals 

Identifies core journals in a subject and their scattering pattern

Zipf;s law

Frequency of words

Studies the frequency distribution of words in a text.

Alan Pritchard Bibliometrics 1969

Earlier term Statistical bibliography used before Bibliometrics

 

Daily reading

 Canons are fundamental rules of classification

Three planes: Idea, Verbal, Notational 

idea plane deals with concepts

verbal plane deals with terminology

Notational plane deals with symbols

Facet analysis breaks complex subjects into facets,

Round = recurrence of a category

Whole organ principle. whole precedes part. 

Rounds and Levels

 

Rounds and Levels

A Fundamental category may occur more than once in a subject

Round: Recurrence of a fundamental category within a round

Ex. In a subject like education of women in India Personality and Space may occur at different levels 

Daily reading

Facet analysis

Breaks a complex subjects into its constituent facets

Helps in identifying different concepts and their relationships

Essential for constructing a class number in faceted scheme like colon classification

 

Daily Reading

 Idea Plane..........Concepts, characteristics and their organization

Verbal Plane............Terminology used to express concepts

Notational Plane..........Symbols used to represent subjects 

Daily Reading

 Principles of facet sequence

Wall picture Principle If one concept cannot exist without another the dependents(picture) comes after the supporting (wall)

Whole organ principle: The whole precedes its part or organ

Cow Calf Principle: The dependent entity (calf) follows the main entity (cow)

Actand-Action-Actor-Tool Principle. Sequence among the entities involved in one action

 

Daily Reading

 PMEST

Ranganathan identified five fundamental categories to analyses subjects

Personality                The main subject/ entity

Matter                       Material, property or substance

Energy                      Action, operation, process

Space                       Geographical manifestation

Time                        Chronological manifestation

Daily reading

 Canons of classification

A canon is fundamental rule or normatiive principle used in designing and evaluating a classification scheme

Formulated by S. R. Ranganathan

canons guide the construction and maintenance of good classification system

Daily Reading

 Primary vs Secondary Sources

Primary Sources                                            Secondary Sources

                                                                                                 

Original Research Paper                                                                            Text Books               

Thesis                                                                                                         Encyclopaedia

Patent                                                                                                         Review Article

Interview Recording                                                                                  Bibliography

Research Report                                                                                        Index

Diary                                                                                                         Biography 

Daily News

Air force veteran appointed first Ram Temple Trust CEO

 

Daily News

Article 142: Supreme court power to ensure complete justice.

NCLT special bench stays relief to Subhas Chandra.    

 

Daily in news

BRICS 

Brazil

Russia

India

China

South Africa 

Later added 

Egypt 

Ethopia

Indonesia

Iran

UAE

Saudi Arabia

BRICS also has 10 partner countries: Belarus, Bolivia, Cuba, Kazakhstan, Malaysia, Nigeria, Thailand, Uganda, Uzbekistan and Vietnam. These are partners, not full members.

Daily Quiz

Q. According to WHO what is the recommended percentage of cesarian delivery.

10 to 15 percent 

DPSP under which section of state to promote cooperative societies

Article 43 (A)